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Thiele's PIDE for unit-linked policies in the Heston-Hawkes stochastic volatility model
David R. Baños / Oriol Zamora Font / Salvador Ortiz-Latorre
insurance / partial differential equationsResource overview

Thiele's PIDE for unit-linked policies in the Heston-Hawkes stochastic volatility model

Paper2023

by David R. Baños, Oriol Zamora Font, Salvador Ortiz-Latorre

Tags
insurancepartial differential equationsstochastic processes

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Suggested foundations for volatility models and surfaces and risk measurement and stress. Specialist prerequisites vary by paper.

Before you read

  1. Stochastic Processes, Brownian Motion and Itô's Lemma

    Follow diffusion-based models and their assumptions.

  2. ARCH and GARCH

    Separate conditional volatility from observed returns.

  3. Random Variables and Distributions

    Represent losses as a distribution rather than one forecast.

  4. Expected Shortfall and Other Tail Risk Measures

    Distinguish a loss quantile from the average loss in the tail.

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  1. Stochastic Volatility and the Heston Model

    Study a correlated stochastic-variance model.

  2. Reading the Implied Vol Surface — Moneyness, Term Structure, and Quoting Conventions

    Interpret prices across strikes and expiries.

  3. VaR Estimation in Practice: Variance-Covariance, Historical Simulation, Monte Carlo

    Compare risk estimators and their assumptions.

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